Long Memory and the Relation between Implied and Realized Volatility

By F. Bandi, B. Perron. 2006

128 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/db0df67cdbb008c02fb67a2bf2be52c84ee20255

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Citations in the corpus

Volatility in Equilibrium: Asymmetries and Dynamic Dependencies (2009, unknown): “We subsequently show how to adjust the model to incorporate empirically relevant long-memory dependencies, while preserving the key return/volatility implications of the initial model.”
Semiparametric inference in multivariate fractionally cointegrated systems (2010, unknown): “This arose in Robinson (1994a), and it has been stressed in a finance context by Bandi and Perron (2004) and Christensen and Nielsen (2006). A larger class (where δr0 > 1/2 is possible) consists of cases where the cointegrating gap (the difference between the integration order of the observables and”
Risk and return: Long-run relations, fractional cointegration, and return predictability $ (2013, methodology): “The fact that vdt exhibits less persistence than the two individual variance series has previously been documented with daily and lower frequency data by Christensen and Nielsen (2006), Bandi and Perron (2006), and Chernov (2007), among others.(4) To establish a similar long-run relation between our”
Volatility puzzles: a simple framework for gauging return-volatility regressions (2006, unknown): “most empirical studies report statistically significant biases in the direction of f040 and f1o1: These empirical biases have in part been explained by a standard errorsin-variables type problem arising from the use of a finite-sample equivalent to the population regression in (16) (Christensen and ”
Fully modified narrow‐band least squares estimation of weak fractional cointegration (2011, unknown): “Recent contributions by, e.g., Comte & Renault (1998), Bandi & Perron (2006), Christensen & Nielsen (2006), and Berger, Chaboud & Hjalmarsson (2009) including empirical evidence, have pointed towards viewing the predictive regression between implied volatility (IV) and realized volatility (RV) as…”
On the Role of Risk Premia in Volatility Forecasting (2007, methodology): “Bandi and Perron (2001) explored the possibility of the fractionally cointegrating relationship between realized and implied volatility (Christensen and Nielsen 2007 performed a similar analysis). Although they found that “a long-run one-to-one correspondence between implied and realized volatility ”
Local Whittle Analysis of Stationary Fractional Cointegration and the Implied–Realized Volatility Relation (2007, methodology): “, Andersen, Bollerslev, Diebold, and Ebens 2001; Bandi and Perron 2004; Christensen and Nielsen 2006), spot prices for crude oil (Robinson and Yajima 2002), and electricity spot prices (Haldrup and Nielsen 2006). In particular, it is the relevant region for the volatility processes I study in my emp”
Refined Inference on Long Memory in Realized Volatility (2008, unknown): “Bandi and Perron (2001) considered spectral methods in estimation, whereas for forecasting, Deo et al. (2004) suggested a long memory stochastic volatility model.”
A Test Against Spurious Long Memory (2011, methodology): “The variance of the measurement error is set equal to the variance of the zt component, following the simulation design of Bandi and Perron (2006).”
Exact local Whittle estimation of fractionally cointegrated systems (2012, background): “Section 6 pro- vides an empirical application that revisits the fractional cointegration analysis between implied and realized volatility by Bandi and Perron (2006).”
Modeling and predicting the CBOE market volatility index (2014, background): “See, among others, Canina and Figlewski (1993), Christensen and Prabhala (1998), Fleming (1998), Blair, Poon and Taylor (2001ab)), Martens and Zein (2004) Koopman, Jungbacker and Hol (2005), and Bandi and Perron (2006).”
Microstructure Noise, Realized Variance, and Optimal Sampling (2008, background): “For potential nonstationarities in volatility, see Bandi and Perron (2006) and the references therein.”